
For example, deployment constraints may require prediction latency below a
threshold. Business constraints may require highly accurate pipelines with explicitly bounded false positive rate – false positives may
deny loans to eligible applicants, which is lost business and could violate
anti-discriminatory requirements. Pursuing fair AI, regulators may require
that any deployed ML pipeline explicitly satisfies bias constraints
[1]}.
